Hi George,
   I did not get an attachment.
   My first step would be to try simplifying things. Do all of these work?

fit_1=glm(Base[,2]~Base[,1],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,10],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,11],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,12],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,13],family=binomial(link="logit"))

This is not a large dataset. That said, if your computer is nearly out of 
memory, even a small dataset might be too much. It might have plenty of 
physical memory, but also lots of (open files, cookies, applications, other 
stuff) that eat memory.

Regards,
Tim



-----Original Message-----
From: R-help <r-help-boun...@r-project.org> On Behalf Of George Brida
Sent: Friday, November 11, 2022 4:17 PM
To: r-help@r-project.org
Subject: [R] Logistic regression for large data

[External Email]

Dear R users,

I have a database  called Base.csv   (attached to this email) which
contains 13 columns and 8257 rows and whose the first 8 columns are dummy 
variables which take 1 or 0. The problem is when I wrote the following 
instructions to do a logistic regression , R runs for hours and hours without 
giving an output:

Base=read.csv("C:\\Users\\HP\\Desktop\\New\\Base.csv",header=FALSE,sep=";")
fit_1=glm(Base[,2]~Base[,1]+Base[,10]+Base[,11]+Base[,12]+Base[,13],family=binomial(link="logit"))

Apparently, there is not enough memory to have the requested output. Is there 
any other function for logistic regression that handle large data and return 
output in reasonable time.

Many thanks

Kind regards

George
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